Antimicrobial Peptides and Activities

Marsupial immune protection is shaped by enhancer sharing and gene cluster duplication of cathelicidin antimicrobial peptides

The paper investigates how marsupial neonates use cathelicidin antimicrobial peptides for immune protection through genomic clustering and enhancer sharing, showing their effectiveness in a sepsis model.

An antibody-drug conjugate exploiting a bacterial immune evasion mechanism is effective against multidrug resistant Neisseria gonorrhoeae

This paper develops an antibody-drug conjugate targeting Neisseria gonorrhoeae that uses bacterial immune evasion to selectively kill drug-resistant strains.

Time-resolved phenotyping at subcellular resolution reveals shared principles and key trade-offs across antimicrobial peptide activities

The paper develops a time-resolved single-cell pipeline to analyze antimicrobial peptides in E. coli, revealing two classes with opposing functional trade-offs in their mechanisms and efficacy against biofilms.

AIPAMPDS: an AI platform for antimicrobial peptide design and screening

AIPAMPDS designs and screens antimicrobial peptides using AI, identifying 10 lead peptides with high antimicrobial activity and low hemolysis.

Mining the UniProtKB/Swiss-Prot database forantimicrobial peptides

The paper identifies novel antimicrobial peptides from the UniProtKB/Swiss-Prot database using AMPlify, prioritizing 40 for chicken applications and testing 38 for antimicrobial activity.

Proteasome-derived antimicrobial peptides discovered via deep learning

The paper uses deep learning to identify novel antimicrobial peptides from proteasomal cleavage products, finding 21 sequence-diverse peptides with potential therapeutic applications against drug-resistant pathogens.

Exploring the repository of de novo designed bifunctional antimicrobial peptides through deep learning

This paper designs bifunctional antimicrobial peptides using deep learning, discovering 16 peptides with both antibacterial and antiviral activity, including two validated against drug-resistant bacteria and viruses.

Harnessing Generative Pre-trained Transformer for Antimicrobial Peptide Generation and MIC Prediction with Contrastive Learning

This paper introduces AMPCLGPT, a model that generates antimicrobial peptides and predicts their MIC values using contrastive learning and pre-training.

AMP-Atlas: Comprehensive Atlas of Antimicrobial Peptides to Combat Multidrug-resistant Bacteria

AMP-Atlas uses AI to predict antimicrobial peptides from sequences, outperforming existing methods and identifying new candidates in human bacteria.

The antimicrobial peptides pipeline: a bacteria-centric AMP predictor

The paper introduces a bacteria-centric AMP predictor that identifies more bacterial antimicrobial peptides from real genomes than fake ones, outperforming existing predictors.

Endogenous antimicrobial peptides in human colostrum: a peptidomics study by liquid-chromatography high-resolution mass-spectrometry (LC-HRMS) and bioinformatics

This study identifies and characterizes antimicrobial peptides in human colostrum using LC-HRMS and bioinformatics, revealing novel peptides with potential antifungal activity.

Structural and Functional Versatility of the Amyloidogenic Antimicrobial Peptide Citropin 1.3

This study investigates the structural and functional properties of citropin 1.3, an antimicrobial peptide from the Southern bell frog, revealing its ability to form distinct fibrillar structures and interact with membranes and cells.

SEVI Fibrils are Induced by Bacterial Surface Molecules and Exert Antimicrobial Activity Against ESKAPE Pathogens

This study shows SEVI fibrils have antibacterial activity against urogenital pathogens and are induced by bacterial surface molecules.

Lasso peptides sviceucin and siamycin I have anti-virulence activity and restore vancomycin effectiveness in vancomycin-resistant Enterococcus sp. and Staphylococcus aureus

This study shows that lasso peptides sviceucin and siamycin I reduce virulence and restore vancomycin effectiveness against resistant bacteria by targeting histidine kinases.

Leveraging Drosophila Models to Explore AI-generated Synthetic Peptide's Potential in Boosting Honeybee Health and Resilience

This study identifies a synthetic peptide, PAN4, with antimicrobial, stress-tolerant, and anti-tumor properties in Drosophila, showing potential for improving honeybee health and resilience.

Design of multimodal antibiotics using deep learning

This paper introduces ApexDuo, a deep learning model that generates peptides with both cell-penetrating and antimicrobial properties, and demonstrates its effectiveness against intracellular pathogens.

Antifungal activity of protamine

This study investigates protamine's antifungal activity against Candida species, finding it inhibits growth and causes membrane rupture and ROS induction.

Chickpea NCR13 disulfide cross-linking variants exhibit profound differences in antifungal activity and modes of action

This study shows that different disulfide bond pairings in chickpea NCR13 peptides lead to distinct antifungal activities and modes of action.

The role of secondary structures of peptide polymers on antimicrobial efficacy and antibiotic potentiation

This study shows that helical peptide polymers enhance antibiotic efficacy against multidrug-resistant bacteria by 2-256-fold while maintaining low toxicity.

SAMP: Identifying Antimicrobial Peptides by an Ensemble Learning Model Based on Proportionalized Split Amino Acid Composition

SAMP identifies antimicrobial peptides using an ensemble model with new features, outperforming existing methods on multiple datasets.

ProT-Diff: A Modularized and Efficient Approach to De Novo Generation of Antimicrobial Peptide Sequences through Integration of Protein Language Model and Diffusion Model

ProT-Diff generates novel antimicrobial peptides using a protein language model and diffusion model, producing 34 active peptides against bacteria with low toxicity.

High Throughput Meta-analysis of Antimicrobial Peptides for Characterizing Class Specific Therapeutic Candidates: An in-silico Approach

The paper performs a meta-analysis of 8.6 million antimicrobial peptides to identify class-specific therapeutic candidates using machine learning and structural analysis.

Multiplexing bacteriocin synthesis to kill and prevent antimicrobial resistance

The paper develops bacteriocin cocktails using cell-free synthesis to target and eliminate antibiotic-resistant bacteria, demonstrating effectiveness in vivo.

Subclass IId bacteriocins targeting Man-PTS--structural diversity and implications for receptor interaction and antimicrobial activity

This paper classifies subclass IId bacteriocins based on sequence similarities and identifies Man-PTS as a receptor, revealing structural diversity and interaction mechanisms.

Anti-Candida and antibiofilm activity of epinecidin-1 and its variants

The paper evaluates anti-Candida and antibiofilm activity of epinecidin-1 and its variants, finding variant-2 most effective with reduced MICs and biofilm disruption.

Prediction of inhibitory peptides against E. coli with desired MIC value

The paper develops a model to predict MIC values of peptides against E. coli using machine learning and a web server for peptide design.

Antimicrobial Profile from Frog Skin Peptides

This study evaluates the antimicrobial efficacy of frog skin peptides against bacteria and fungi, finding Magainin 2 and Bombesin effective against Bacillus subtilis, Escherichia coli, and Trichoderma harzianum.

Alpha-defensin binding expands human adenovirus tropism

This paper shows that human adenoviruses can bind to cells via alpha-defensins instead of their usual receptors, expanding their tropism to non-susceptible cells.

Nanoliter-scale selection of optimized bioengineered peptide antibiotics that rescue mice with bacterial lung infection

This study uses a mutasynthetic library to identify optimized darobactin derivatives that effectively treat bacterial lung infections in mice.

Recombinant expression, purification, and antifungal activity of the novel antimicrobial peptide TaW662

This study identifies and characterizes TaW662, an antifungal peptide from wheat, showing inhibition of Blumeria graminis f. sp. tritici growth and potential as a fungicide.